Banking on Nature | Quantifying Nature Risk towards Credit Risk Decisions

Written by Sourajit Aiyer, Insight Contributor and author of the Banking on Nature series at In|Flow

For banks, nature risk is increasingly recognised as a driver of financial risk that impacts borrower cash flows, asset quality and capital requirements. Analysis shows over 50% of global GDP is moderately or highly dependent on nature (WEF, 2020), with ecosystem dependencies in several sectors including agriculture, food, infrastructure, and real estate. This translates directly into sectoral credit concentration risks and forward-looking asset quality concerns for banks. The developing countries are most vulnerable, since they lack adequate adaptive capacity to withstand shocks.

In such countries, banks manage the major share of financial assets. They face a challenge to quantify the impact of nature risk on their internal risk rating, probability of default, loss given default, and loan pricing decisions. Nature risk is multi-dimensional, location-specific and lacks a single metric equivalent to emissions. This complexity makes it challenging for banks to embed such risks into their internal rating models, credit underwriting templates, and translate them into financial ratios for credit committees. The core challenge for bankers is not awareness; but converting ecological signals into decision-useful credit metrics within existing systems.

Translating nature risk to credit metrics

The starting point for a bank is the elements of exposure, hazard and vulnerability, similar to the process of climate risk assessment. Hazard in the case of nature risks relates to ecological triggers, like water scarcity, soil degradation, deforestation, drop in pollination, flood protection, regulatory restrictions, etc. that are material to the region. Research by the Food & Agriculture Organisation (FAO), UN Environment, the Asian Development Bank (ADB) and others, may offer sufficiently robust proxy datasets for first-level quantification without requiring complex ecological modelling.

Exposure in nature risks is about identifying which components of the bank’s portfolio are most dependent on ecological triggers material to the region. Portfolio exposures may be clustered around sectors and regions, and further overlaid with ecological stress maps or datasets from publicly available tools such as ENCORE, the WWF Risk Filter, IBAT(Integrated Biodiversity Assessment Tool) or the World Resource Institute (WRI)’s Aqueduct. These available datasets may enable first-order quantification, without sophisticated ecological modelling.

This level of quantification enables the bank to identify the level of vulnerability and concentration risk. For example, the percentage of loan book exposed to locations classified as water stress regions, or at a more granular level, the percentage of its sectoral loan book exposed to specific high-stress locations. 

This step is critical as it converts nature risk into measurable portfolio concentration metrics that can be tracked and reported.

Once these metrics integrated into existing credit models and sustainable lending, the bank may develop nature risk scorecards to complement traditional credit templates. The nature risk scorecard may assign rank-based dependency scores based on the findings from the sector and location analysis. Over time, such scorecards can be embedded into credit policy and sector guidelines, in turn fostering consistency across transactions.

Empowered with a more comprehensive risk assessment, the bank can use these to influence the credit risk analysis. For example, if a large borrower in a high-stress sector like agriculture operates in a water-stress region estimated to see a percentage reduction in freshwater availability over a specific time period, the bank can enquire how this reduction in freshwater availability would impact the yield, revenue and operating costs for that borrower.

The question becomes, would an X% drop in freshwater lead to a Y% drop in yield, and a commensurate Y% drop in revenue (assuming prices remain constant)? At the same time, would the operating cost rise by Z% owing to higher cost to procure freshwater from alternate sources? This conversion enables nature risk to enter financial models in a structured and replicable way.

For the bank’s perspective, the resulting impact on the borrower’s operating profit would lead to revising its forecasted cash flows, interest coverage ratio (ICR), and debt service coverage ratio. The bank may want to stress test the borrower’s financial projections against these quantified shocks derived from risk scores from the nature risk scorecard, and observe the impact on the borrower’s leverage, interest coverage and liquidity ratios. 

A drop in ICR and other ratios can then be translated into risk rating adjustments, by conducting a suitable risk-notch downgrade against its internal risk rating thresholds. Based on the revised risk rating and the historical credit default data pertaining to that rating level, the appropriate pricing may be reflected, or subsequent adjustments made to covenants or tenor. 

These adjustments reflect where nature risk begins to influence real-world financial decisions.

For sanctioned lending facilities, a great deal depends on the flexibility offered by those structures; but at least these processes could be integrated into new loan sanctions, as a start.

The bank must also consider regulatory-related factors. For borrowers that need to meet new rules related to deforestation-free supply chains, sustainable sourcing, etc., additional compliance in terms of traceability processes and reporting may add to costs, thus impacting cash flows. Such regulatory shifts are increasingly being driven by frameworks like CBD  and TNFD and will likely tighten over time. If such compliance costs were to be added to capital expenditure for new projects, they may increase leverage ratios and extend the time required to bring debt down, thereby impacting pricing estimations.

At a broader level, ideally, such quantification should not just influence the rating for a transaction, but the broader portfolio alignment and capital allocation strategy. For example, if a bank estimates X% of its loan book is exposed to regions exposed to an ecological trigger, leading to a drop in stressed coverage ratios falling below Y, this may justify revising capital allocation limits, higher margins, or requiring shorter tenors, risk mitigation measures, or conditions precedent. 

Greater clarity may form the basis for incentivising borrowers to invest in resource efficiency measures leading to tackling that particular trigger, ultimately leading to greater resilience. 

Such borrowers may be incentivised through better pricing terms, or even LMA-aligned sustainability-linked loan structures tied to predefined ecological indicators. This is where nature risk transitions from a defensive risk tool to a driver of strategic portfolio allocation. Select banks have begun to take steps towards linking ecological indicators and financial outcomes. Triodos Bank integrated biodiversity impact and dependency assessments into its agriculture and forestry lending, using ecological indicators within underwriting. HSBC published guidance on integrating nature considerations in agricultural and forestry into risk management, linking environment issues with credit processes. 

In conclusion, the process involves identification of exposure and dependency, scoring the material impacts using public data, adjusting the borrowers’ financial projections and the banks’ credit metrics. Financial flows will consider the potential downside from nature risk only when it impacts credit operating model and portfolio asset quality through risk ratings, pricing, covenants or capital requirements. The transition from awareness to integration is therefore the defining step for banks.

References: 

Food and Agriculture Organization. (2021). The state of the world’s land and water resources for food and agriculture – Systems at breaking point (SOLAW 2021). FAO.

Natural Capital Finance Alliance. (2022). ENCORE: Exploring Natural Capital Opportunities, Risks and Exposure – Tool and methodology. NCFA.

Taskforce on Nature-related Financial Disclosures. (2023). Recommendations of the Taskforce on Nature-related Financial Disclosures. TNFD.

United Nations Environment Programme. (2021). Making peace with nature: A scientific blueprint to tackle the climate, biodiversity and pollution emergencies. UNEP.

World Economic Forum. (2020). Nature risk rising: Why the crisis engulfing nature matters for business and the economy. WEF.

World Resources Institute. (2019). Aqueduct water risk atlas: Technical note. WRI.

WWF. (2020). Nature is too big to fail: Biodiversity – the next frontier in financial risk management. WWF.